Bayesian quantile-regression tools for dynamic state-space models and static regression under the extended asymmetric Laplace error distribution (exAL).
Dynamic/state-space quantile modeling via
exdqlmLDVB() and exdqlmMCMC(), with legacy exdqlmISVB()
retained for backward compatibility and transfer-function extensions
through exdqlmTransferLDVB(), exdqlmTransferMCMC(), and legacy
exdqlmTransferISVB().
Static Bayesian exAL regression via exalStaticLDVB() and
exalStaticMCMC().
Modular state-space construction via polytrendMod(), seasMod(),
and regMod().
Multi-quantile post-processing via
quantileSynthesis() for post hoc posterior-predictive
synthesis from separately fitted quantiles into a unified
predictive distribution.
Dynamic Bayesian quantile state-space inference with LDVB as the main VB engine, MCMC for posterior simulation, and legacy ISVB retained for compatibility and historical comparisons.
A unified package covering both dynamic exDQLM models and static exAL regression.
Static shrinkage priors including ridge, regularized horseshoe
("rhs"), and rhs_ns.
Reduced AL/DQLM paths through dqlm.ind = TRUE in both dynamic and
static APIs.
Standardized VB diagnostics traces via
fit$diagnostics$vb_trace for ELBO, sigma, gamma, and
convergence deltas across VB engines.
Conservative automatic warmup defaults for the most failure-prone
shared blocks: RHS-family tau scheduling plus exAL
(sigma, gamma) warmup in VB and MCMC entry points, with explicit
controls available only when users need to override the defaults.
Optional C++ acceleration for selected state-space computations.
options(exdqlm.use_cpp_kf = TRUE|FALSE) – C++ Kalman bridge (optional; default TRUE).
options(exdqlm.compute_elbo = TRUE|FALSE) – Compute ELBO (optional; default TRUE).
options(exdqlm.tol_elbo = numeric) – Positive ELBO convergence tolerance used when
exdqlm.compute_elbo = TRUE; smaller values enforce stricter ELBO stabilization checks
(default 1e-6).
options(exdqlm.use_cpp_builders = TRUE|FALSE) – C++ model builders (optional; default FALSE).
options(exdqlm.use_cpp_samplers = TRUE|FALSE) – C++ samplers (optional; default FALSE).
options(exdqlm.use_cpp_postpred = TRUE|FALSE) – C++ posterior predictive sampler (optional; default FALSE).
options(exdqlm.use_cpp_mcmc = TRUE|FALSE) – MCMC backend routing (optional; default TRUE).
options(exdqlm.cpp_mcmc_mode = "strict"|"fast") – strict keeps legacy R-kernel parity; fast enables C++ FFBS in MCMC (default "fast").
options(exdqlm.cpp_threads = numeric) – Positive integer thread cap for eligible
OpenMP-enabled C++ paths (1L forces single-thread; default 1L).
Maintainer: Raquel Barata raquel.a.barata@gmail.com
Authors:
Antonio Aguirre
Other contributors:
Raquel Prado [thesis advisor]
Bruno Sanso [thesis advisor]
The package centers on native dynamic quantile state-space modeling for
univariate time series, while version 0.4.0 also provides a static exAL
regression workflow. Across these settings, exdqlm combines model
construction helpers, multiple Bayesian inference engines, shrinkage priors
for static coefficients, and post hoc synthesis of several fitted quantiles.
Useful links: